Description
Do you want to get into machine learning but do not know where to start? This is a 3-day course with a practical approach to machine learning directed to PhD students at the Faculty of Medicine. The course includes two days of lectures from basics about machine learning to application of models and critical interpretation of the results. Students will be able to work on their own data (or data provided by the lecturers) based on learnings from the first two days and on the third day, results, and plans for optimizing their results will be discussed.
The content of the course is:
· Getting started with machine learning
· Extracting information from data and identifying the most relevant sources (Feature extraction and reduction of
feature space)
· Classification and regression models
· Evaluating the performance of a model
· Working with own data
The lecturers will use Python in teaching, but the principles and concepts are easily transferred to other environments, such as, R, Matlab, etc.
Literature
Links to pre read distributed in Moodle by the different lecturers in due time before the course.
Prerequisites
An education in health sciences and basic knowledge about statistical concepts.
Evaluation
The student will be evaluated individually through their work with own data or data provided by the lecturers.
Organisers: Thomas Kronborg Larsen, email: tkl@hst.aau.dk
Flemming Witt Udsen, email: fwu@hst.aau.dk
Nynne Sophie Holdt-Caspersen, email: nyhc@novonordisk.com
Morten Hasselstrøm Jensen, email: mhj@hst.aau.dk
ECTS: 2.0
Dates: 16, 17 November and 14 December 2023 (08:15-16:15)
Place: Aalborg University, Selma Lagerløfs Vej 249
16 November: Room 11.00.034
17 November: Room 11.00.035
14 December: Room 11.00.034
Deadline: 26 October 2023
Program: BEN
Important information concerning PhD courses:
We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.
- Teacher: Thomas Kronborg Larsen